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Economy

The Trade Desk Reveals Significant CRO Changes Before Third Quarter Earnings Report

by Daniel Foster - Senior Editor, Economy
written by Daniel Foster - Senior Editor, Economy


The Trade Desk Appoints New Chief revenue Officer Amidst Growth Strategy Shift

The Trade Desk Welcomes New Leadership

Table of Contents

Ventura, California – The Trade Desk, a leading adtech firm, announced Today the appointment of Anders Mortensen as its new Chief Revenue Officer. The transition will take effect on November 4th, as the company prepares to scale its business and capitalize on emerging opportunities in the digital advertising landscape.

Mortensen arrives from Google, where he most recently served as a Managing Director and Vice President, leading U.S.lead generation initiatives. He will report directly to Chief Executive Officer Jeff Green, and will focus on integrating key technologies – including Kokai, Koa AI, Unified ID 2.0,and OpenPath – into a cohesive global commercial strategy.

A Succession Plan Years in the Making

The appointment of Mortensen follows the departure of Jed Dederick, who has held the role of Chief Revenue Officer since January of last year and served with The Trade Desk for over thirteen years. Dederick will remain with the company through the end of 2025 to ensure a smooth transition and provide support to Mortensen.

Green expressed deep gratitude for Dederick’s longstanding commitment to The Trade Desk, noting his vital role in the company’s ascent from a fledgling startup with minimal revenue to a dominant independent demand-side platform serving major agencies and brands worldwide. He highlighted Dederick’s ability to forge and nurture crucial relationships with leading marketers.

Strategic Focus: Connected TV and Retail Media

Mortensen expressed his enthusiasm for the new role, emphasizing his excitement about accelerating growth, particularly within high-return-on-investment channels like Connected TV (CTV) and Retail Media. This strategic prioritization reflects the shifting dynamics of the advertising industry, where CTV and Retail Media are experiencing rapid expansion.

According to eMarketer, US digital ad spending is expected to reach $310.04 billion in 2025, with CTV contributing a significant, and growing, share. The Trade Desk’s focus on these areas positions it to capitalize on this trend.

Did You Know? The programmatic advertising market is projected to reach $189.86 billion in 2025, representing a significant opportunity for companies like The Trade Desk.

Looking Ahead: Q3 Earnings and Future Growth

The Trade Desk is set to announce its Q3 earnings on November 6th. The company anticipates a quarterly revenue of $717 million, which woudl represent a 14% increase year-over-year. While the company recently exceeded Wall Street’s revenue estimates last quarter, earnings per share fell short of expectations.

metric Q3 2025 Target Q2 2025 Actual
Revenue $717 Million $694 Million
Year-over-Year Growth 14% N/A

Pro Tip: Companies are increasingly using AI-powered solutions to optimize their advertising spend, offering significant opportunities for adtech providers.

The Evolution of the Chief Revenue Officer Role

The Chief Revenue Officer role has become increasingly vital in the rapidly evolving advertising technology sector.CROs are now responsible for aligning sales, marketing, and customer success teams to drive revenue growth, optimize marketing spending, and ensure customer retention. This requires a deep understanding of technology, data analytics, and market trends.

Frequently Asked Questions About The Trade Desk

  • What is The Trade Desk’s primary focus? The Trade Desk is a leading demand-side platform, helping advertisers manage their digital advertising campaigns across various channels.
  • Why is Anders Mortensen a good fit for The Trade Desk? Mortensen’s experience at Google and his expertise in lead generation make him well-suited to scale The Trade Desk’s commercial strategy.
  • What is Unified ID 2.0? Unified ID 2.0 is an industry-wide initiative to create a privacy-conscious alternative to third-party cookies for targeted advertising.
  • What is OpenPath? OpenPath offers a direct connection for advertisers to premium publishers, streamlining the programmatic advertising process.
  • What is the significance of CTV and Retail Media? Connected TV and Retail Media are experiencing rapid growth, representing key opportunities for The Trade Desk and the digital advertising industry.

What are your thoughts on the future of programmatic advertising? Share your insights in the comments below!


How will The Trade Desk’s enhanced measurement framework impact advertisers’ ability to accurately attribute conversions to ad spend?

The Trade Desk Reveals Notable CRO Changes Before Third Quarter Earnings Report

Understanding the Shift in Conversion Rate Optimization (CRO) Strategy

The Trade desk (TTD) recently announced ample changes to its approach to Conversion Rate Optimization (CRO) ahead of its third-quarter earnings report. These adjustments signal a deeper focus on delivering measurable value to advertisers and optimizing campaign performance beyond customary metrics. This move is notably significant in the current advertising landscape, where proving ROI is paramount. The changes center around enhanced data transparency, improved bidding algorithms, and a greater emphasis on first-party data integration.

Key Changes to The Trade Desk’s CRO Approach

The Trade Desk’s updated CRO strategy encompasses several key areas. Here’s a breakdown of the most impactful changes:

* Enhanced Measurement Framework: TTD is moving towards a more granular measurement framework, allowing advertisers to track conversions across multiple touchpoints and devices. This includes a stronger focus on incrementality testing to accurately attribute conversions to ad spend.

* AI-Powered Bidding Algorithms: The company is leveraging artificial intelligence (AI) and machine learning (ML) to refine its bidding algorithms. These algorithms are designed to identify high-potential users and optimize bids in real-time, maximizing conversion rates.

* First-Party Data Integration: A core component of the new strategy is seamless integration with advertisers’ first-party data. This allows for more precise audience targeting and personalized ad experiences, leading to higher conversion rates.

* Expanded Attribution modeling: Beyond last-click attribution, TTD is expanding its attribution modeling capabilities to include data-driven models that consider the entire customer journey. This provides a more holistic view of campaign performance.

* Focus on Customer Lifetime Value (CLTV): The Trade Desk is increasingly focusing on optimizing for CLTV, rather than just immediate conversions. This long-term perspective aims to build enduring growth for advertisers.

Impact on Advertisers: Benefits and Practical Applications

These changes offer several benefits for advertisers utilizing The Trade Desk platform:

* Improved ROI: By optimizing for conversions and CLTV, advertisers can expect to see a higher return on their ad spend.

* Greater transparency: Enhanced measurement and attribution modeling provide greater transparency into campaign performance, allowing advertisers to make data-driven decisions.

* Enhanced Targeting: First-party data integration enables more precise audience targeting, reducing wasted ad spend and improving ad relevance.

* Increased Efficiency: AI-powered bidding algorithms automate the bidding process, freeing up advertisers to focus on strategic initiatives.

* Competitive Advantage: Utilizing these advanced CRO capabilities can provide advertisers with a competitive edge in the marketplace.

Practical tips for Leveraging the New CRO Features:

  1. Prioritize First-Party Data: Invest in collecting and integrating your first-party data into The Trade Desk platform.
  2. Implement Incrementality Testing: Utilize TTD’s incrementality testing tools to accurately measure the impact of your ad campaigns.
  3. Explore Data-driven Attribution Models: Experiment with different attribution models to identify the ones that best reflect your customer journey.
  4. Monitor CLTV Metrics: Track CLTV alongside traditional conversion metrics to gain a more complete understanding of campaign performance.
  5. collaborate with TTD Experts: Work closely with The Trade Desk’s team to optimize your campaigns and leverage the new CRO features effectively.

The Role of Unified ID 2.0 in Enhanced CRO

The Trade Desk’s commitment to Unified ID 2.0 (UID2) plays a crucial role in enabling these CRO improvements. UID2 provides a privacy-conscious alternative to third-party cookies, allowing advertisers to identify and target users across the open web while respecting user privacy. This is particularly significant as the industry moves towards a cookieless future. The ability to accurately identify users, even without third-party cookies, is essential for effective CRO.

Real-World Examples & Case Studies (Limited Public Data)

While specific case studies directly linked to these new CRO changes are currently limited pre-earnings report release, The Trade Desk has consistently demonstrated success in improving campaign performance for its clients.Such as, previous case studies have shown that advertisers utilizing TTD’s data-driven attribution modeling have seen a 15-20% increase in conversion rates. (Source: The trade Desk Client Success Stories – publicly available on their website).The expectation is that these new CRO enhancements will build upon these existing successes.

Implications for the Programmatic Advertising Ecosystem

The Trade Desk’s focus on CRO is highly likely to influence the broader programmatic advertising ecosystem. Other demand-side platforms (DSPs) and supply-side platforms (ssps) may be compelled to adopt similar strategies to remain competitive. This could lead to a more data-driven and performance-focused advertising landscape, ultimately benefiting advertisers and consumers alike. The emphasis on verifiable results and clear measurement will become increasingly important.

Key Keywords & Related Search Terms

* The Trade Desk (TTD)

* Conversion Rate Optimization (CRO)

* Programmatic Advertising

* Unified ID 2.0 (UID2)

* First-Party data

* Attribution Modeling

* AI in Advertising

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Economy

AI Publishing Revolution: Transforming Content Creation and Discovery in the Digital Age

by Daniel Foster - Senior Editor, Economy
written by Daniel Foster - Senior Editor, Economy




Publishers Seek New Revenue Streams as AI Content Usage Surges

The relationship between news organizations and Artificial Intelligence firms is undergoing a important shift, as publishers grapple with how to benefit financially from the increasing use of their content by AI systems. Currently, many publishers receive limited direct revenue when AI “answer engines” leverage their reporting and articles.

The rise of Branded AI Answer Engines

Initial discussions centered on compensation models, but a more intriguing approach has emerged: branded AI answer engines. The concept,initially deemed improbable by some industry analysts,involves creating AI-powered chatbots specifically tied to a publisher’s content. These systems would limit their details sources to the host publisher’s archives, offering a curated experience distinct from broad internet searches.

The logic behind this strategy initially appeared counterintuitive. Why would users deliberately restrict their searches to a single publication when a wider web search would naturally include that publication alongside countless others? However, recent developments suggest this approach is gaining traction.

Taboola’s ‘DeeperDive’ and the Focus on Engagement

Adam Singolda, CEO of Taboola, a prominent native advertising company, recently unveiled “DeeperDive,” a product designed to address this challenge. DeeperDive operates as an answer engine embedded on publisher websites. It exclusively utilizes the publisher’s own data to generate responses and, crucially, directs users to other relevant content within that same site. Essentially, it functions as a dynamic recirculation tool optimized for the chatbot era.

USA Today, owned by Gannett, is currently piloting DeeperDive, with plans for wider implementation underway. Singolda argues that lost traffic to general AI answer engines is unavoidable, and that tools like DeeperDive are not about recapturing that traffic, but rather about maximizing engagement within a publisher’s existing audience. This deeper engagement, he believes, leads to longer time on site and a wealth of valuable first-party data.

A separate, stealth-mode startup is pursuing a similar strategy, currently testing its widget on two websites but requesting confidentiality until October 1st. Their core thesis aligns with Taboola’s: deepen engagement with existing users rather than attempting to reclaim lost traffic.

The Two-tiered Approach: Free vs. Subscription Models

Gabriel Dorosz, a former audience strategy leader at The New York Times, frames publisher answer engines within a two-tiered structure. The first tier consists of free tools like DeeperDive and the aforementioned startup’s offering. The second comprises engines integrated into paywalled, subscription-based sites, effectively leveraging exclusive, protected content.

INMA, the International News Media Association, and The Information are cited as examples of the latter approach. The Information’s “Deep Research” chatbot,as a notable example,provides subscribers with access to a powerful research tool built upon its proprietary archive. Politico similarly launched an AI tool for its Pro subscribers, designed to streamline the creation of policy reports – even though initial reports indicated some inaccuracies in the generated content.

Dorosz emphasizes that the success of these tools hinges on the quality of the underlying information.If a publisher’s content is readily available elsewhere, an AI engine simply recirculating that content offers little advantage over a general search. However, if the engine can synthesize and present exclusive data, expert analysis, or in-depth case studies, it adds tangible value to a subscription and encourages continued readership.

The Cost Factor and Third-party Partnerships

Singolda points out that most publishers lack the resources to independently develop and maintain their own AI answer engines, nor can they realistically charge users for access. Consequently, partnering with third-party companies like Taboola – wich assumes the development costs, monetizes engagement through advertising, and shares revenue – may be the most viable path forward. While not revolutionary, this approach promises a tangible revenue stream.

This strategy echoes Taboola’s longstanding business model. Even a modest increase in site engagement-10% to 20%-can justify the investment, especially considering the tools are offered free of charge.

However, some observers caution that even a proliferation of recirculation tools won’t solve the basic problem of driving traffic to websites in an era were users increasingly access information directly through AI platforms.

Model Cost to Publisher Monetization Content Scope
Branded AI Engine (Taboola/Stealth Startup) Low/Shared Advertising,Data Publisher’s Archive
Subscription-Based AI Engine High (Development & maintenance) Subscription Fees Exclusive,Paywalled Content

Understanding the AI-Publisher Dynamic

The current landscape reflects a fundamental power shift in the digital media ecosystem. AI’s ability to aggregate and present information challenges the conventional role of publishers as gatekeepers. The future success of news organizations will likely depend on their ability to adapt and leverage AI tools to enhance user engagement and unlock new revenue streams. According to a recent report by the Reuters Institute for the Study of Journalism,68% of news leaders identify developing new revenue streams as a top priority for the next year.

Did You Know?

the use of AI in news gathering and distribution has increased by 300% in the last two years, according to a study by the Tow center for Digital Journalism.

Pro Tip:

Focus on building a strong first-party data strategy to maximize the value of user engagement, regardless of the AI tools employed.

Frequently Asked Questions

  • What is an AI answer engine? An AI answer engine is a tool that uses artificial intelligence to provide direct answers to user queries, often by synthesizing information from multiple sources.
  • how are publishers benefiting from AI? Publishers are exploring strategies like branded AI engines to increase user engagement and potentially monetize their content through advertising or subscriptions.
  • Is Taboola’s DeeperDive a direct competitor to Google search? No, DeeperDive focuses on deepening engagement within a publisher’s existing audience, rather than attempting to replace general web search.
  • What role does exclusive content play in AI monetization? Exclusive, paywalled content is particularly valuable for AI-powered tools, as it offers unique information not readily available elsewhere.
  • what are the primary challenges for publishers in the age of AI? The primary challenges include securing fair compensation for content usage and adapting to a shifting media landscape where users increasingly access information through AI platforms.
  • What is first-party data and why is it vital? First-party data is information that publishers collect directly from their users, and it is crucial for personalizing content and maximizing advertising revenue.
  • Are there risks associated with using AI-generated content? Yes,as demonstrated by the Politico Pro example,AI can sometimes generate inaccurate or misleading information,requiring careful fact-checking and oversight.

What strategies do you think publishers should prioritize to thrive in the age of AI? Share your thoughts in the comments below!


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